#!/usr/bin/env python """ Parts of this file were taken from the pyzmq project (https://github.com/zeromq/pyzmq) which have been permitted for use under the BSD license. Parts are from lxml (https://github.com/lxml/lxml) """ import os import sys import shutil import warnings try: BUILD_CACHE_DIR=None # uncomment to activate the build cache #BUILD_CACHE_DIR="/tmp/.pandas_build_cache/" if os.isdir(BUILD_CACHE_DIR): print("--------------------------------------------------------") print("BUILD CACHE ACTIVATED. be careful, this is experimental.") print("--------------------------------------------------------") else: BUILD_CACHE_DIR=None except : pass # may need to work around setuptools bug by providing a fake Pyrex try: import Cython sys.path.insert(0, os.path.join(os.path.dirname(__file__), "fake_pyrex")) except ImportError: pass # try bootstrapping setuptools if it doesn't exist try: import pkg_resources try: pkg_resources.require("setuptools>=0.6c5") except pkg_resources.VersionConflict: from ez_setup import use_setuptools use_setuptools(version="0.6c5") from setuptools import setup, Command _have_setuptools = True except ImportError: # no setuptools installed from distutils.core import setup, Command _have_setuptools = False setuptools_kwargs = {} if sys.version_info[0] >= 3: setuptools_kwargs = {'use_2to3': True, 'zip_safe': False, 'install_requires': ['python-dateutil >= 2', 'pytz', 'numpy >= 1.4'], 'use_2to3_exclude_fixers': ['lib2to3.fixes.fix_next', ], } if not _have_setuptools: sys.exit("need setuptools/distribute for Py3k" "\n$ pip install distribute") else: if sys.version_info[1] == 5: # dateutil >= 2.1 doesn't work on Python 2.5 setuptools_kwargs = { 'install_requires': ['python-dateutil < 2', 'pytz', 'numpy >= 1.6'], 'zip_safe' : False, } else: setuptools_kwargs = { 'install_requires': ['python-dateutil', 'pytz', 'numpy >= 1.6'], 'zip_safe' : False, } if not _have_setuptools: try: import numpy import dateutil setuptools_kwargs = {} except ImportError: sys.exit("install requires: 'python-dateutil < 2','numpy'." " use pip or easy_install." "\n $ pip install 'python-dateutil < 2' 'numpy'") try: import numpy as np except ImportError: nonumpy_msg = ("# numpy needed to finish setup. run:\n\n" " $ pip install numpy # or easy_install numpy\n") sys.exit(nonumpy_msg) if np.__version__ < '1.6.1': msg = "pandas requires NumPy >= 1.6 due to datetime64 dependency" sys.exit(msg) from distutils.extension import Extension from distutils.command.build import build from distutils.command.sdist import sdist from distutils.command.build_ext import build_ext try: from Cython.Distutils import build_ext #from Cython.Distutils import Extension # to get pyrex debugging symbols cython=True except ImportError: cython=False from os.path import splitext, basename, join as pjoin DESCRIPTION = ("Powerful data structures for data analysis, time series," "and statistics") LONG_DESCRIPTION = """ **pandas** is a Python package providing fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, **real world** data analysis in Python. Additionally, it has the broader goal of becoming **the most powerful and flexible open source data analysis / manipulation tool available in any language**. It is already well on its way toward this goal. pandas is well suited for many different kinds of data: - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure The two primary data structures of pandas, Series (1-dimensional) and DataFrame (2-dimensional), handle the vast majority of typical use cases in finance, statistics, social science, and many areas of engineering. For R users, DataFrame provides everything that R's ``data.frame`` provides and much more. pandas is built on top of `NumPy `__ and is intended to integrate well within a scientific computing environment with many other 3rd party libraries. Here are just a few of the things that pandas does well: - Easy handling of **missing data** (represented as NaN) in floating point as well as non-floating point data - Size mutability: columns can be **inserted and deleted** from DataFrame and higher dimensional objects - Automatic and explicit **data alignment**: objects can be explicitly aligned to a set of labels, or the user can simply ignore the labels and let `Series`, `DataFrame`, etc. automatically align the data for you in computations - Powerful, flexible **group by** functionality to perform split-apply-combine operations on data sets, for both aggregating and transforming data - Make it **easy to convert** ragged, differently-indexed data in other Python and NumPy data structures into DataFrame objects - Intelligent label-based **slicing**, **fancy indexing**, and **subsetting** of large data sets - Intuitive **merging** and **joining** data sets - Flexible **reshaping** and pivoting of data sets - **Hierarchical** labeling of axes (possible to have multiple labels per tick) - Robust IO tools for loading data from **flat files** (CSV and delimited), Excel files, databases, and saving / loading data from the ultrafast **HDF5 format** - **Time series**-specific functionality: date range generation and frequency conversion, moving window statistics, moving window linear regressions, date shifting and lagging, etc. Many of these principles are here to address the shortcomings frequently experienced using other languages / scientific research environments. For data scientists, working with data is typically divided into multiple stages: munging and cleaning data, analyzing / modeling it, then organizing the results of the analysis into a form suitable for plotting or tabular display. pandas is the ideal tool for all of these tasks. Note ---- Windows binaries built against NumPy 1.6.1 """ DISTNAME = 'pandas' LICENSE = 'BSD' AUTHOR = "The PyData Development Team" EMAIL = "pydata@googlegroups.com" URL = "http://pandas.pydata.org" DOWNLOAD_URL = '' CLASSIFIERS = [ 'Development Status :: 4 - Beta', 'Environment :: Console', 'Operating System :: OS Independent', 'Intended Audience :: Science/Research', 'Programming Language :: Python', 'Programming Language :: Python :: 2', 'Programming Language :: Python :: 3', 'Programming Language :: Cython', 'Topic :: Scientific/Engineering', ] MAJOR = 0 MINOR = 9 MICRO = 1 ISRELEASED = True VERSION = '%d.%d.%d' % (MAJOR, MINOR, MICRO) QUALIFIER = '' FULLVERSION = VERSION if not ISRELEASED: FULLVERSION += '.dev' try: import subprocess try: pipe = subprocess.Popen(["git", "rev-parse", "--short", "HEAD"], stdout=subprocess.PIPE).stdout except OSError: # msysgit compatibility pipe = subprocess.Popen(["git.cmd", "rev-parse", "--short", "HEAD"], stdout=subprocess.PIPE).stdout rev = pipe.read().strip() # makes distutils blow up on Python 2.7 if sys.version_info[0] >= 3: rev = rev.decode('ascii') FULLVERSION += "-%s" % rev except: warnings.warn("WARNING: Couldn't get git revision") else: FULLVERSION += QUALIFIER def write_version_py(filename=None): cnt = """\ version = '%s' short_version = '%s' """ if not filename: filename = os.path.join(os.path.dirname(__file__), 'pandas', 'version.py') a = open(filename, 'w') try: a.write(cnt % (FULLVERSION, VERSION)) finally: a.close() class CleanCommand(Command): """Custom distutils command to clean the .so and .pyc files.""" user_options = [("all", "a", "") ] def initialize_options(self): self.all = True self._clean_me = [] self._clean_trees = [] self._clean_exclude = ['np_datetime.c', 'np_datetime_strings.c', 'period.c'] for root, dirs, files in list(os.walk('pandas')): for f in files: if f in self._clean_exclude: continue if os.path.splitext(f)[-1] in ('.pyc', '.so', '.o', '.pyd', '.c', '.orig'): self._clean_me.append(pjoin(root, f)) for d in dirs: if d == '__pycache__': self._clean_trees.append(pjoin(root, d)) for d in ('build',): if os.path.exists(d): self._clean_trees.append(d) def finalize_options(self): pass def run(self): for clean_me in self._clean_me: try: os.unlink(clean_me) except Exception: pass for clean_tree in self._clean_trees: try: shutil.rmtree(clean_tree) except Exception: pass class CheckSDist(sdist): """Custom sdist that ensures Cython has compiled all pyx files to c.""" _pyxfiles = ['pandas/src/tseries.pyx' 'pandas/src/sparse.pyx'] def initialize_options(self): sdist.initialize_options(self) ''' self._pyxfiles = [] for root, dirs, files in os.walk('pandas'): for f in files: if f.endswith('.pyx'): self._pyxfiles.append(pjoin(root, f)) ''' def run(self): if 'cython' in cmdclass: self.run_command('cython') else: for pyxfile in self._pyxfiles: cfile = pyxfile[:-3]+'c' msg = "C-source file '%s' not found."%(cfile)+\ " Run 'setup.py cython' before sdist." assert os.path.isfile(cfile), msg sdist.run(self) class CheckingBuildExt(build_ext): """Subclass build_ext to get clearer report if Cython is necessary.""" def check_cython_extensions(self, extensions): for ext in extensions: for src in ext.sources: if not os.path.exists(src): raise Exception("""Cython-generated file '%s' not found. Cython is required to compile pandas from a development branch. Please install Cython or download a release package of pandas. """ % src) def build_extensions(self): self.check_cython_extensions(self.extensions) self.check_extensions_list(self.extensions) for ext in self.extensions: self.build_extension(ext) class CompilationCacheMixin(object): def __init__(self,*args,**kwds): cache_dir=kwds.pop("cache_dir",BUILD_CACHE_DIR) self.cache_dir=cache_dir if not os.path.isdir(cache_dir): raise Exception("Error: path to Cache directory (%s) is not a dir" % cache_dir); def _copy_from_cache(self,hash,target): src=os.path.join(self.cache_dir,hash) if os.path.exists(src): # print("Cache HIT: asked to copy file %s in %s" % (src,os.path.abspath(target))) s="." for d in target.split(os.path.sep)[:-1]: s=os.path.join(s,d) if not os.path.exists(s): os.mkdir(s) shutil.copyfile(src,target) return True return False def _put_to_cache(self,hash,src): target=os.path.join(self.cache_dir,hash) # print( "Cache miss: asked to copy file from %s to %s" % (src,target)) s="." for d in target.split(os.path.sep)[:-1]: s=os.path.join(s,d) if not os.path.exists(s): os.mkdir(s) shutil.copyfile(src,target) def _hash_obj(self,obj): """ you should override this method to provide a sensible implementation of hashing functions for your intended objects """ try: return hash(obj) except: raise NotImplementedError("You must override this method") # this is missing in 2.5, mro will do the right thing def get_ext_fullpath(self, ext_name): """Returns the path of the filename for a given extension. The file is located in `build_lib` or directly in the package (inplace option). """ import string # makes sure the extension name is only using dots all_dots = string.maketrans('/'+os.sep, '..') ext_name = ext_name.translate(all_dots) fullname = self.get_ext_fullname(ext_name) modpath = fullname.split('.') filename = self.get_ext_filename(ext_name) filename = os.path.split(filename)[-1] if not self.inplace: # no further work needed # returning : # build_dir/package/path/filename filename = os.path.join(*modpath[:-1]+[filename]) return os.path.join(self.build_lib, filename) # the inplace option requires to find the package directory # using the build_py command for that package = '.'.join(modpath[0:-1]) build_py = self.get_finalized_command('build_py') package_dir = os.path.abspath(build_py.get_package_dir(package)) # returning # package_dir/filename return os.path.join(package_dir, filename) class CompilationCacheExtMixin(CompilationCacheMixin): def __init__(self,*args,**kwds): CompilationCacheMixin.__init__(self,*args,**kwds) def _hash_file(self,fname): from hashlib import sha1 try: hash=sha1() hash.update(self.build_lib.encode('utf-8')) try: if sys.version_info[0] >= 3: import io f=io.open(fname,"rb") else: f=open(fname) first_line=f.readline() # ignore cython generation timestamp header if "Generated by Cython" not in first_line.decode('utf-8'): hash.update(first_line) hash.update(f.read()) return hash.hexdigest() except: raise return None finally: f.close() except IOError: return None def _hash_obj(self,ext): from hashlib import sha1 sources = ext.sources if sources is None or \ (not hasattr(sources,'__iter__') ) or \ isinstance(sources,str) or \ sys.version[0]==2 and isinstance(sources,unicode): #argh return False sources = list(sources) + ext.depends hash=sha1() try: for fname in sources: fhash=self._hash_file(fname) if fhash: hash.update(fhash.encode('utf-8')) except: return None return hash.hexdigest() class CachingBuildExt(build_ext,CompilationCacheExtMixin): def __init__(self,*args,**kwds): CompilationCacheExtMixin.__init__(self,*args,**kwds) kwds.pop("cache_dir",None) build_ext.__init__(self,*args,**kwds) def build_extension(self, ext,*args,**kwds): ext_path = self.get_ext_fullpath(ext.name) build_path = os.path.join(self.build_lib,os.path.basename(ext_path)) hash=self._hash_obj(ext) if hash and self._copy_from_cache(hash,ext_path): return build_ext.build_extension(self,ext,*args,**kwds) hash=self._hash_obj(ext) if os.path.exists(build_path): self._put_to_cache(hash,build_path) # build_ext if os.path.exists(ext_path): self._put_to_cache(hash,ext_path) # develop def cython_sources(self, sources, extension): import re cplus = self.cython_cplus or getattr(extension, 'cython_cplus', 0) or \ (extension.language and extension.language.lower() == 'c++') target_ext = '.c' if cplus: target_ext = '.cpp' for i,s in enumerate(sources): if not re.search("\.(pyx|pxi|pxd)$",s): continue ext_dir=os.path.dirname(s) ext_basename=re.sub("\.[^\.]+$","",os.path.basename(s)) ext_basename += target_ext target= os.path.join(ext_dir,ext_basename) hash=self._hash_file(s) sources[i]=target if hash and self._copy_from_cache(hash,target): continue build_ext.cython_sources(self,[s],extension) self._put_to_cache(hash,target) return sources class CythonCommand(build_ext): """Custom distutils command subclassed from Cython.Distutils.build_ext to compile pyx->c, and stop there. All this does is override the C-compile method build_extension() with a no-op.""" def build_extension(self, ext): pass class DummyBuildSrc(Command): """ numpy's build_src command interferes with Cython's build_ext. """ user_options = [] def initialize_options(self): self.py_modules_dict = {} def finalize_options(self): pass def run(self): pass cmdclass = {'clean': CleanCommand, 'build': build} if cython: suffix = '.pyx' cmdclass['build_ext'] = build_ext if BUILD_CACHE_DIR: # use the cache cmdclass['build_ext'] = CachingBuildExt cmdclass['cython'] = CythonCommand cmdclass['sdist'] = CheckSDist else: suffix = '.c' cmdclass['build_src'] = DummyBuildSrc cmdclass['build_ext'] = build_ext tseries_depends = ['reindex', 'groupby', 'skiplist', 'moments', 'reduce', 'stats', 'datetime', 'hashtable', 'inference', 'properties', 'join', 'engines'] plib_depends = ['plib'] def srcpath(name=None, suffix='.pyx', subdir='src'): return pjoin('pandas', subdir, name+suffix) if suffix == '.pyx': tseries_depends = [srcpath(f, suffix='.pyx') for f in tseries_depends] tseries_depends.append('pandas/src/util.pxd') plib_depends = [srcpath(f, suffix='.pyx') for f in plib_depends] plib_depends.append('pandas/src/util.pxd') else: tseries_depends = [] plib_depends = [] algos_ext = Extension('pandas._algos', sources=[srcpath('generated', suffix=suffix)], include_dirs=[np.get_include()]) lib_depends = tseries_depends + ['pandas/src/numpy_helper.h', 'pandas/src/datetime/np_datetime.h', 'pandas/src/datetime/np_datetime_strings.h'] # some linux distros require it libraries = ['m'] if 'win32' not in sys.platform else [] lib_ext = Extension('pandas.lib', depends=lib_depends, sources=[srcpath('tseries', suffix=suffix), 'pandas/src/datetime/np_datetime.c', 'pandas/src/datetime/np_datetime_strings.c'], include_dirs=[np.get_include()], libraries=libraries, # pyrex_gdb=True, # extra_compile_args=['-Wconversion'] ) sparse_ext = Extension('pandas._sparse', sources=[srcpath('sparse', suffix=suffix)], include_dirs=[np.get_include()], libraries=libraries) period_ext = Extension('pandas._period', depends=plib_depends + ['pandas/src/numpy_helper.h', 'pandas/src/period.h'], sources=[srcpath('plib', suffix=suffix), 'pandas/src/datetime/np_datetime.c', 'pandas/src/period.c'], include_dirs=[np.get_include()]) sandbox_ext = Extension('pandas._sandbox', sources=[srcpath('sandbox', suffix=suffix)], include_dirs=[np.get_include()]) cppsandbox_ext = Extension('pandas._cppsandbox', language='c++', sources=[srcpath('cppsandbox', suffix=suffix)], include_dirs=[np.get_include()]) extensions = [algos_ext, lib_ext, period_ext, sparse_ext] if not ISRELEASED: extensions.extend([sandbox_ext]) if suffix == '.pyx' and 'setuptools' in sys.modules: # undo dumb setuptools bug clobbering .pyx sources back to .c for ext in extensions: if ext.sources[0].endswith('.c'): root, _ = os.path.splitext(ext.sources[0]) ext.sources[0] = root + suffix if _have_setuptools: setuptools_kwargs["test_suite"] = "nose.collector" write_version_py() setup(name=DISTNAME, version=FULLVERSION, maintainer=AUTHOR, packages=['pandas', 'pandas.compat', 'pandas.core', 'pandas.io', 'pandas.rpy', 'pandas.sandbox', 'pandas.sparse', 'pandas.sparse.tests', 'pandas.stats', 'pandas.util', 'pandas.tests', 'pandas.tools', 'pandas.tools.tests', 'pandas.tseries', 'pandas.tseries.tests', 'pandas.io.tests', 'pandas.stats.tests', ], package_data={'pandas.io' : ['tests/*.h5', 'tests/*.csv', 'tests/*.xls', 'tests/*.xlsx', 'tests/*.table'], 'pandas.tools': ['tests/*.csv'], 'pandas.tests' : ['data/*.pickle', 'data/*.csv'], 'pandas.tseries.tests' : ['data/*.pickle', 'data/*.csv'] }, ext_modules=extensions, maintainer_email=EMAIL, description=DESCRIPTION, license=LICENSE, cmdclass = cmdclass, url=URL, download_url=DOWNLOAD_URL, long_description=LONG_DESCRIPTION, classifiers=CLASSIFIERS, platforms='any', **setuptools_kwargs)